ArticleBMJ open2019
Association between disease-modifying therapies for multiple sclerosis and healthcare utilisation on a population level: a retrospective cohort study.
Article in BMJ open, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- Reasons for Hospital Admission in Individuals With Multiple Sclerosis.International journal of MS care · 2024Article
- Disease-modifying drugs for multiple sclerosis and subsequent health service use.Multiple sclerosis (Houndmills, Basingstoke, England) · 2022Article
- Disease-Modifying Drug Uptake and Health Service Use in the Ageing MS Population.Frontiers in immunology · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveDisease-modifying therapy (DMT) use in multiple sclerosis (MS) has increased significantly. However, the impact of DMTs on healthcare use is limited and conflicting, and rarely examined at a population level. This study examined the association between DMTs and healthcare utilisation at the population level.
designRetrospective cohort.
settingHealth administrative data from Saskatchewan, Canada (1997-2016).
participantsTo test for associations at the population level, we identified two cohorts. The general population cohort included all Saskatchewan residents ≥18 years who were drug plan beneficiaries. The MS cohort included individuals ≥18 years, identified using a validated definition (≥3 hospital, physician or drug claims for MS). MAIN OUTCOME MEASURES AND
methodsTo test for an association between the total number of DMT dispensations per year and the total number of hospitalisations we used negative binomial regression fitted with generalised estimating equations (GEE); only hospitalisations that occurred after the date of MS diagnosis (date of first claim for MS or demyelinating disease) were extracted. To test for an association between the number of DMT dispensations and physician claims, negative binomial distributions with GEE were fit as above. Results were reported as rate ratios (RR), with 95% CIs, and calculated for every 1000 DMT dispensations.
resultsThe number of DMT dispensations was associated with a decreased risk for all-cause (RR=0.994; 95% CI 0.992 to 0.996) and MS-specific (RR=0.909; 95% CI 0.880 to 0.938) hospitalisations. The number of DMT dispensations was not associated with the number of all-cause (RR=1.006; 95% CI 0.990 to 1.022) or MS-specific (RR=0.962; 95% CI 0.910 to 1.016) physician claims.
conclusionIncreased DMT use in Saskatchewan was associated with a reduction in hospitalisations, but did not impact the number of physician services used. Additional research on cost-benefit and differing treatment strategies would provide further insight into the true impact of DMTs on healthcare utilisation at a population level.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.